Random number generators (RNGs) are important for numerous applications including medicine, cryptography (for example Quantum Key Distribution), information security, gaming, lotteries and scientific simulation. “Pseudo-RNGs” are based on computer algorithms, which eventually repeat themselves. Physical RNGs however are based on the unpredictable outcomes of physical measurements, and therefore the quality of the randomness is higher. For generators based on quantum mechanics (QRNGs), unpredictability can be derived rigorously from first principles and therefore these RNGs can offer random numbers of highest quality. The quality of randomness impacts the performance of the application. For example, for cryptography there is a need for high quality randomness in order that the cryptographic service provides strong protection.
For many applications, there is a need for a high speed real-time feed of random numbers. For example, Quantum Key Distribution (QKD) applications may require ultrafast feeds of random numbers at a rate on the order of 1-10 Gb/s.